The test expected content=None to immediately trigger thinking-exhaustion,
but PR #7738 correctly gates that check on _has_think_tags. Without think
tags, the agent falls through to normal continuation retry (3 attempts).
When API routers rewrite finish_reason from "length" to "tool_calls",
truncated JSON arguments bypassed the length handler and wasted 3
retry attempts in the generic JSON validation loop. Now detects
truncation patterns in tool call arguments regardless of finish_reason.
Fixes#7680
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Background process watchers (notify_on_complete, check_interval) created
synthetic SessionSource objects without user_id/user_name. While the
internal=True bypass (1d8d4f28) prevented false pairing for agent-
generated notifications, the missing identity caused:
- Garbage entries in pairing rate limiters (discord:None, telegram:None)
- 'User None' in approval messages and logs
- No user identity available for future code paths that need it
Additionally, platform messages arriving without from_user (Telegram
service messages, channel forwards, anonymous admin actions) could still
trigger false pairing because they are not internal events.
Fix:
1. Propagate user_id/user_name through the full watcher chain:
session_context.py → gateway/run.py → terminal_tool.py →
process_registry.py (including checkpoint persistence/recovery)
2. Add None user_id guard in _handle_message() — silently drop
non-internal messages with no user identity instead of triggering
the pairing flow.
Salvaged from PRs #7664 (kagura-agent, ContextVar approach),
#6540 (MestreY0d4-Uninter, tests), and #7709 (guang384, None guard).
Closes#6341, #6485, #7643
Relates to #6516, #7392
Two-phase design so the warning fires before the user's first message
on every platform:
Phase 1 (__init__):
_check_compression_model_feasibility() runs during agent construction.
Resolves the auxiliary compression model (same chain as call_llm with
task='compression'), compares its context length to the main model's
compression threshold. If too small, emits via _emit_status() (prints
for CLI) and stores the warning in _compression_warning.
Phase 2 (run_conversation, first call):
_replay_compression_warning() re-sends the stored warning through
status_callback — which the gateway wires AFTER construction. The
warning is then cleared so it only fires once.
This ensures:
- CLI users see the warning immediately at startup (right after the
context limit line)
- Gateway users (Telegram, Discord, Slack, WhatsApp, Signal, Matrix,
Mattermost, Home Assistant, DingTalk, etc.) receive it via
status_callback('lifecycle', ...) on their first message
- logger.warning() always hits agent.log regardless of platform
Also warns when no auxiliary LLM provider is configured at all.
Entire check wrapped in try/except — never blocks startup.
11 tests covering: core warning logic, boundary conditions, exception
safety, two-phase store+replay, gateway callback wiring, and
single-delivery guarantee.
The Weixin adapter was splitting responses at every top-level newline,
causing notification spam (up to 70 API calls for a single long markdown
response). This salvages the best aspects of six contributor PRs:
Compact mode (new default):
- Messages under the 4000-char limit stay as a single bubble even with
multiple lines, paragraphs, and code blocks
- Only oversized messages get split at logical markdown boundaries
- Inter-chunk delay (0.3s) between chunks prevents WeChat rate-limit drops
Legacy mode (opt-in):
- Set split_multiline_messages: true in platforms.weixin.extra config
- Or set WEIXIN_SPLIT_MULTILINE_MESSAGES=true env var
- Restores the old per-line splitting behavior
Salvaged from PRs #7797 (guantoubaozi), #7792 (luoxiao6645),
#7838 (qyx596), #7825 (weedge), #7784 (sherunlock03), #7773 (JnyRoad).
Core fix unanimous across all six; config toggle from #7838; inter-chunk
delay from #7825.
Independent halving of width and height caused aspect ratio distortion
for extreme dimensions (e.g. 8000x200 panoramas). When one axis hit the
64px floor, the other kept shrinking — collapsing the ratio toward 1:1.
Use proportional scaling instead: when either dimension hits the floor,
derive the effective scale factor and apply it to both axes.
Add tests for extreme panorama (8000x200) and tall narrow (200x6000)
images to verify aspect ratio preservation.
hermes claw migrate now always shows a full dry-run preview before
making any changes. The user reviews what would be imported, then
confirms to proceed. --dry-run stops after the preview. --yes skips
the confirmation prompt.
This matches the existing setup wizard flow (_offer_openclaw_migration)
which already did preview-then-confirm.
Docs updated across both docs/migration/openclaw.md and
website/docs/guides/migrate-from-openclaw.md to reflect:
- New preview-first UX flow
- workspace-main/ fallback paths
- accounts.default channel token layout
- TTS edge/microsoft rename
- openclaw.json env sub-object as API key source
- Hyphenated provider API types
- Matrix accessToken field
- SecretRef file/exec warnings
- Skills session restart note
- WhatsApp re-pairing note
- Archive cleanup step
Cherry-picked from PR #7702 by kshitijk4poor.
Adds Xiaomi MiMo as a direct provider (XIAOMI_API_KEY) with models:
- mimo-v2-pro (1M context), mimo-v2-omni (256K, multimodal), mimo-v2-flash (256K, cheapest)
Standard OpenAI-compatible provider checklist: auth.py, config.py, models.py,
main.py, providers.py, doctor.py, model_normalize.py, model_metadata.py,
models_dev.py, auxiliary_client.py, .env.example, cli-config.yaml.example.
Follow-up: vision tasks use mimo-v2-omni (multimodal) instead of the user's
main model. Non-vision aux uses the user's selected model. Added
_PROVIDER_VISION_MODELS dict for provider-specific vision model overrides.
On failure, falls back to aggregators (gemini flash) via existing fallback chain.
Corrects pre-existing context lengths: mimo-v2-pro 1048576→1000000,
mimo-v2-omni 1048576→256000, adds mimo-v2-flash 256000.
36 tests covering registry, aliases, auto-detect, credentials, models.dev,
normalization, URL mapping, providers module, doctor, aux client, vision
model override, and agent init.
Cherry-picked from PR #7749 by kshitijk4poor with modifications:
- Raise hard image limit from 5 MB to 20 MB (matches most restrictive provider)
- Send images at full resolution first; only auto-resize to 5 MB on API failure
- Add _is_image_size_error() helper to detect size-related API rejections
- Auto-resize uses Pillow (soft dep) with progressive downscale + JPEG quality reduction
- Fix get_model_capabilities() to check modalities.input for vision support
- Increase default vision timeout from 30s to 120s (matches hardcoded fallback intent)
- Applied retry-with-resize to both vision_analyze_tool and browser_vision
Closes#7740
Matrix gateway: fix sync loop never dispatching events (#5819)
- _sync_loop() called client.sync() but never called handle_sync()
to dispatch events to registered callbacks — _on_room_message was
registered but never fired for new messages
- Store next_batch token from initial sync and pass as since= to
subsequent incremental syncs (was doing full initial sync every time)
- 17 comments, confirmed by multiple users on matrix.org
Feishu docs: add interactive card configuration for approvals (#6893)
- Error 200340 is a Feishu Developer Console configuration issue,
not a code bug — users need to enable Interactive Card capability
and configure Card Request URL
- Added required 3-step setup instructions to feishu.md
- Added troubleshooting entry for error 200340
- 17 comments from Feishu users
Copilot provider drift: detect GPT-5.x Responses API requirement (#3388)
- GPT-5.x models are rejected on /v1/chat/completions by both OpenAI
and OpenRouter (unsupported_api_for_model error)
- Added _model_requires_responses_api() to detect models needing
Responses API regardless of provider
- Applied in __init__ (covers OpenRouter primary users) and in
_try_activate_fallback() (covers Copilot->OpenRouter drift)
- Fixed stale comment claiming gateway creates fresh agents per message
(it caches them via _agent_cache since the caching was added)
- 7 comments, reported on Copilot+Telegram gateway
* fix(matrix): pass required args to MemoryCryptoStore for mautrix ≥0.21
MemoryCryptoStore.__init__() now requires account_id and pickle_key
positional arguments as of mautrix 0.21. The migration from matrix-nio
(commit 1850747) didn't account for this, causing E2EE initialization
to fail with:
MemoryCryptoStore.__init__() missing 2 required positional arguments:
'account_id' and 'pickle_key'
Pass self._user_id as account_id and derive pickle_key from the same
user_id:device_id pair already used for the on-disk HMAC signature.
Update the test stub to accept the new parameters.
Fixes#7803
* fix: use consistent fallback for pickle_key derivation
Address review: _pickle_key now uses _acct_id (which has the 'hermes'
fallback) instead of raw self._user_id, so both values stay consistent
when user_id is empty.
---------
Co-authored-by: Hermes Agent <hermes@nousresearch.com>
Based on PR #7285 by @kshitijk4poor.
Two bugs affecting Qwen OAuth users:
1. Wrong context window — qwen3-coder-plus showed 128K instead of 1M.
Added specific entries before the generic qwen catch-all:
- qwen3-coder-plus: 1,000,000 (corrected from PR's 1,048,576 per
official Alibaba Cloud docs and OpenRouter)
- qwen3-coder: 262,144
2. Random stopping — max_tokens was suppressed for Qwen Portal, so the
server applied its own low default. Reasoning models exhaust that on
thinking tokens. Now: honor explicit max_tokens, default to 65536
when unset.
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
* feat: add watch_patterns to background processes for output monitoring
Adds a new 'watch_patterns' parameter to terminal(background=true) that
lets the agent specify strings to watch for in process output. When a
matching line appears, a notification is queued and injected as a
synthetic message — triggering a new agent turn, similar to
notify_on_complete but mid-process.
Implementation:
- ProcessSession gets watch_patterns field + rate-limit state
- _check_watch_patterns() in ProcessRegistry scans new output chunks
from all three reader threads (local, PTY, env-poller)
- Rate limited: max 8 notifications per 10s window
- Sustained overload (45s) permanently disables watching for that process
- watch_queue alongside completion_queue, same consumption pattern
- CLI drains watch_queue in both idle loop and post-turn drain
- Gateway drains after agent runs via _inject_watch_notification()
- Checkpoint persistence + crash recovery includes watch_patterns
- Blocked in execute_code sandbox (like other bg params)
- 20 new tests covering matching, rate limiting, overload kill,
checkpoint persistence, schema, and handler passthrough
Usage:
terminal(
command='npm run dev',
background=true,
watch_patterns=['ERROR', 'WARN', 'listening on port']
)
* refactor: merge watch_queue into completion_queue
Unified queue with 'type' field distinguishing 'completion',
'watch_match', and 'watch_disabled' events. Extracted
_format_process_notification() in CLI and gateway to handle
all event types in a single drain loop. Removes duplication
across both CLI drain sites and the gateway.
Cover all public functions with 50 test cases:
- managed_nous_tools_enabled() feature flag toggling
- normalize_browser_cloud_provider() coercion and defaults
- coerce_modal_mode() / normalize_modal_mode() validation
- has_direct_modal_credentials() env vars and config file detection
- resolve_modal_backend_state() full backend selection matrix
- resolve_openai_audio_api_key() priority chain and edge cases
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Follow-up fixes for cherry-pick conflicts:
- Removed test_context_keeps_pending_approval test that referenced
pop_pending() which doesn't exist on current main
- Added headers attribute to FakeResponse in vision test (needed
after #6949 added Content-Length check)
Three fixes for vision_analyze returning cryptic 400 "Invalid request data":
1. Pre-flight base64 size check — base64 inflates data ~33%, so a 3.8 MB
file exceeds the 5 MB API limit. Reject early with a clear message
instead of letting the provider return a generic 400.
2. Handle file:// URIs — strip the scheme and resolve as a local path.
Previously file:///path/to/image.png fell through to the "invalid
image source" error since it matched neither is_file() nor http(s).
3. Separate invalid_request errors from "does not support vision" errors
so the user gets actionable guidance (resize/compress/retry) instead
of a misleading "model does not support vision" message.
Closes#6677
YAML parses bare numeric keys (e.g. `12306:`) as int, causing
TypeError when sorted() is called on mixed int/str collections.
Changes:
- Normalize toolset_names entries to str in _get_platform_tools()
- Cast MCP server name to str(name) when building enabled_mcp_servers
- Add regression test
Four fixes to auxiliary_client.py:
1. Respect explicit provider as hard constraint (#7559)
When auxiliary.{task}.provider is explicitly set (not 'auto'),
connection/payment errors no longer silently fallback to cloud
providers. Local-only users (Ollama, vLLM) will no longer get
unexpected OpenRouter billing from auxiliary tasks.
2. Eliminate model='default' sentinel (#7512)
_resolve_api_key_provider() no longer sends literal 'default' as
model name to APIs. Providers without a known aux model in
_API_KEY_PROVIDER_AUX_MODELS are skipped instead of producing
model_not_supported errors.
3. Add payment/connection fallback to async_call_llm (#7512)
async_call_llm now mirrors sync call_llm's fallback logic for
payment (402) and connection errors. Previously, async consumers
(session_search, web_tools, vision) got hard failures with no
recovery. Also fixes hardcoded 'openrouter' fallback to use the
full auto-detection chain.
4. Use accurate error reason in fallback logs (#7512)
_try_payment_fallback() now accepts a reason parameter and uses
it in log messages. Connection timeouts are no longer misleadingly
logged as 'payment error'.
Closes#7559Closes#7512
The auxiliary client always calls client.chat.completions.create(),
ignoring the api_mode config flag. This breaks codex-family models
(e.g. gpt-5.3-codex) on direct OpenAI API keys, which need the
/v1/responses endpoint.
Changes:
- Expand _resolve_task_provider_model to return api_mode (5-tuple)
- Read api_mode from auxiliary.{task}.api_mode config and env vars
(AUXILIARY_{TASK}_API_MODE)
- Pass api_mode through _get_cached_client to resolve_provider_client
- Add _needs_codex_wrap/_wrap_if_needed helpers that wrap plain OpenAI
clients in CodexAuxiliaryClient when api_mode=codex_responses or
when auto-detection finds api.openai.com + codex model pattern
- Apply wrapping at all custom endpoint, named custom provider, and
API-key provider return paths
- Update test mocks for the new 5-tuple return format
Users can now set:
auxiliary:
compression:
model: gpt-5.3-codex
base_url: https://api.openai.com/v1
api_mode: codex_responses
Closes#6800
_discover_bundled_skills() used the directory name to identify skills,
but skills_tool.py and skills_hub.py use the `name:` field from SKILL.md
frontmatter. This mismatch caused 9 builtin skills whose directory name
differs from their SKILL.md name to be written to .bundled_manifest
under the wrong key, so `hermes skills list` showed them as "local"
instead of "builtin".
Read the frontmatter name field (with directory-name fallback) so the
manifest keys match what the rest of the codebase expects.
Closes#6835
Aligns MiniMax provider with official API documentation. Fixes 6 bugs:
transport mismatch (openai_chat -> anthropic_messages), credential leak
in switch_model(), prompt caching sent to non-Anthropic endpoints,
dot-to-hyphen model name corruption, trajectory compressor URL routing,
and stale doctor health check.
Also corrects context window (204,800), thinking support (manual mode),
max output (131,072), and model catalog (M2 family only on /anthropic).
Source: https://platform.minimax.io/docs/api-reference/text-anthropic-api
Co-authored-by: kshitijk4poor <kshitijk4poor@users.noreply.github.com>
Two fixes for the honcho memory plugin: (1) initOnSessionStart — opt-in eager session init in tools mode so sync_turn() works from turn 1 (default false, non-breaking). (2) peerName fix — gateway user_id no longer silently overwrites an explicitly configured peerName. 11 new tests. Contributed by @Kathie-yu.
_is_oauth_token() returned True for any key not starting with 'sk-ant-api',
which means MiniMax and Alibaba API keys were falsely treated as Anthropic
OAuth tokens. This triggered the Claude Code compatibility path:
- All tool names prefixed with mcp_ (e.g. mcp_terminal, mcp_web_search)
- System prompt injected with 'You are Claude Code' identity
- 'Hermes Agent' replaced with 'Claude Code' throughout
Fix: Make _is_oauth_token() positively identify Anthropic OAuth tokens by
their key format instead of using a broad catch-all:
- sk-ant-* (but not sk-ant-api-*) -> setup tokens, managed keys
- eyJ* -> JWTs from Anthropic OAuth flow
- Everything else -> False (MiniMax, Alibaba, etc.)
Reported by stefan171.
* fix: circuit breaker stops CPU-burning restart loops on persistent errors
When a gateway session hits a non-retryable error (e.g. invalid model
ID → HTTP 400), the agent fails and returns. But if the session keeps
receiving messages (or something periodically recreates agents), each
attempt spawns a new AIAgent — reinitializing MCP server connections,
burning CPU — only to hit the same 400 error again. On a 4-core server,
this pegs an entire core per stuck session and accumulates 300+ minutes
of CPU time over hours.
Fix: add a per-session consecutive failure counter in the gateway runner.
- Track consecutive non-retryable failures per session key
- After 3 consecutive failures (_MAX_CONSECUTIVE_FAILURES), block
further agent creation for that session and notify the user:
'⚠️ This session has failed N times in a row with a non-retryable
error. Use /reset to start a new session.'
- Evict the cached agent when the circuit breaker engages to prevent
stale state from accumulating
- Reset the counter on successful agent runs
- Clear the counter on /reset and /new so users can recover
- Uses getattr() pattern so bare GatewayRunner instances (common in
tests using object.__new__) don't crash
Tests:
- 8 new tests in test_circuit_breaker.py covering counter behavior,
threshold, reset, session isolation, and bare-runner safety
Addresses #7130.
* Revert "fix: circuit breaker stops CPU-burning restart loops on persistent errors"
This reverts commit d848ea7109.
* fix: don't evict cached agent on failed runs — prevents MCP restart loop
When a run fails (e.g. invalid model ID → 400) and fallback activated,
the gateway was evicting the cached agent to 'retry primary next time.'
But evicting a failed agent forces a full AIAgent recreation on the next
message — reinitializing MCP server connections, spawning stdio
processes — only to hit the same 400 again. This created a CPU-burning
loop (91%+ for hours, #7130).
The fix: add `and not _run_failed` to the fallback-eviction check.
Failed runs keep the cached agent. The next message reuses it (no MCP
reinit), hits the same error, returns it to the user quickly. The user
can /reset or /model to fix their config.
Successful fallback runs still evict as before so the next message
retries the primary model.
Addresses #7130.
- Remove unreachable `if not content_sample` branch inside the truthy
`if content_sample` block in `_is_likely_binary()` (dead code that
could never execute).
- Replace `linter_cmd.format(file=...)` with `linter_cmd.replace("{file}", ...)`
in `_check_lint()` so file paths containing curly braces (e.g.
`src/{test}.py`) no longer raise KeyError/ValueError.
- Add 16 unit tests covering both fixes and edge cases.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
GPT-5+ models (except gpt-5-mini) are only accessible via the Responses
API on Copilot. When these models were configured as the compression
summary_model (or any auxiliary task), the plain OpenAI client sent them
to /chat/completions which returned a 400 error:
model "gpt-5.4-mini" is not accessible via the /chat/completions endpoint
resolve_provider_client() now checks _should_use_copilot_responses_api()
for the copilot provider and wraps the client in CodexAuxiliaryClient
when needed, routing calls through responses.stream() transparently.
Adds tests for both the wrapping (gpt-5.4-mini) and non-wrapping
(gpt-4.1-mini) paths.
Add delegation.reasoning_effort config key so subagents can run at a
different thinking level than the parent agent. When set, overrides
the parent's reasoning_config; when empty, inherits as before.
Valid values: xhigh, high, medium, low, minimal, none (disables thinking).
Config path: delegation.reasoning_effort in config.yaml
Files changed:
- tools/delegate_tool.py: resolve override in _build_child_agent
- hermes_cli/config.py: add reasoning_effort to DEFAULT_CONFIG
- tests/tools/test_delegate.py: 4 new tests covering all cases
Follow-up fixes for the matrix-nio → mautrix migration:
1. Module-level mautrix.types import now wrapped in try/except with
proper stub classes. Without this, importing gateway.platforms.matrix
crashes the entire gateway when mautrix isn't installed — even for
users who don't use Matrix. The stubs mirror mautrix's real attribute
names so tests that exercise adapter methods (send, reactions, etc.)
work without the real SDK.
2. Removed _ensure_mautrix_mock() from test_matrix_mention.py — it
permanently installed MagicMock modules in sys.modules via setdefault(),
polluting later tests in the suite. No longer needed since the module
imports cleanly without mautrix.
3. Fixed thread persistence tests to use direct class reference in
monkeypatch.setattr() instead of string-based paths, which broke
when the module was reimported by other tests.
4. Moved the module-importability test to a subprocess to prevent it
from polluting sys.modules (reimporting creates a second module object
with different __dict__, breaking patch.object in subsequent tests).
matrix-nio pulls in peewee -> atomicwrites (sdist-only, archived,
missing build-system metadata) which breaks nix flake builds.
mautrix-python publishes wheels, has a leaner dep tree, and its
[encryption] extra uses the same python-olm without the problematic
transitive chain.
- Add shared is_wsl() to hermes_constants (like is_termux)
- Update supports_systemd_services() to verify systemd is actually
running on WSL before returning True
- Add WSL-specific guidance in gateway install/start/setup/status
for both cases: WSL+systemd and WSL without systemd
- Improve help strings: 'run' now says recommended for WSL/Docker,
'start'/'install' now mention systemd/launchd explicitly
- Add WSL gateway FAQ section with tmux/nohup/Task Scheduler tips
- Update CLI commands docs with WSL tip
- Deduplicate _is_wsl() from clipboard.py to shared hermes_constants
- Fix clipboard tests to reset hermes_constants cache
- 20 new WSL-specific tests covering detection, systemd check,
supports_systemd_services integration, and command output
Motivated by user feedback: took 1 hour to figure out run vs start
on WSL, Telegram bot kept disconnecting due to flaky WSL systemd.
